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Seo Competitors

by io.github.pipeworx-io

Search Within a Source

search_within
Read-onlyIdempotent

Semantic search INSIDE a fetched record. Pass the text you already pulled (e.g. a SEC 10-K body, an article, a long tool result) plus a natural-language query; get back the top-N passages with character offsets and similarity scores. Use when the record is too big to cram into the prompt — search_within saves context, returns only the passages that matter, and every passage carries an offset so the agent can verify a verbatim quote. Pairs with ask_pipeworx_grounded: fetch with the gateway, ground over the relevant passages instead of the whole document. BGE-base-en embeddings + cosine over 500-char overlapping windows; cap is 200K chars (longer inputs are truncated and flagged).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe document text to search inside (max ~200K chars).
limitNoMax passages to return (1-20, default 5).
queryYesNatural-language query — what passages do you want? E.g. "supply-chain risk", "fiscal year 2024 revenue", "drug interactions with warfarin".

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly/openWorld/idempotent; description adds embedding model details (BGE-base-en, cosine, 500-char windows), the 200K char cap with truncation flag, and the guarantee that passages carry offsets for verbatim quote verification. No contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four well-organized sentences; each clause adds value: purpose, use-case, pairing, and technical limits. No filler words; front-loaded with the core function.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (semantic search, windowing, truncation, pairing), the description covers return format (passages, offsets, similarity), max input size, usage context, and relationship to sibling tools. Complete despite no output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers all three parameters with descriptions (100% coverage). Description reinforces with query examples and contextual hints, but adds no major new parameter semantics beyond the schema's existing 'max ~200K chars' and 'natural-language query' definitions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description states 'Semantic search INSIDE a fetched record' with explicit verb+resource, and describes passing text plus query to get passages. It distinguishes from siblings by framing as operating on already-fetched text rather than querying a database.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'Use when the record is too big to cram into the prompt' and explains the pairwise workflow with ask_pipeworx_grounded ('fetch with the gateway, ground over the relevant passages'). This clearly identifies when to use and an alternative integration pattern.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Seo Competitors toolsInspect
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TDQS

A3.8/5.0
Disambiguation2/5

Several tools are near-duplicates or easily confused: ask_pipeworx_beta is explicitly identical to ask_pipeworx, ai_visibility_check overlaps with scan_competitor_ai_presence, and polymarket_edges, polymarket_arbitrage, and bet_research all target opportunity discovery. While many tools are distinct, the boundaries between these clusters are unclear enough to cause misselection.

Naming Consistency4/5

The vast majority of tools use a consistent lowercase snake_case convention with descriptive noun/verb patterns (e.g., polymarket_edges, entity_profile, validate_claim, resolve_entity). Minor deviations like seo_domain_ranked_keywords and ask_pipeworx_beta are slightly off-pattern, but the overall style is predictable.

Tool Count2/5

32 tools is above the threshold where a set starts to feel bloated, especially for a server named "Seo Competitors". The count includes many unrelated subsystems—Polymarket betting, memory, subscriptions, and generic data routing—making it feel like a kitchen sink rather than a focused SEO competitor toolkit.

Completeness2/5

For a server claiming to support SEO competitor analysis, the surface is incomplete: it offers a keyword-ranking tool and AI visibility checks, but lacks standard competitor SEO capabilities like backlink analysis, rank tracking over time, content-gap analysis, or site audits. The broader data/query tooling is extensive, but it doesn't fill the gaps in the advertised domain.

Resources